非接触式可见光-近红外光谱法快速预测天然高分子材料表面粗糙度的研究

利用触针式轮廓法测量了天然高分子材料木材的表面粗糙度,并对可见光-近红外光谱与实测表面粗糙度参数之间的相关性进行研究,探讨了非接触式光谱法快速预测天然高分子材料表面粗糙度的可行性。结果表明：（1）样品三个切面的可见光-近红外光谱（400～2 500 nm）均可预测样品表面粗糙度,实测值与预测值相关系数可达0.92,其中利用样品横切面光谱所建的模型效果最好;（2）在分段光谱400～780 nm,780～1 100 nm,1 100～2 500 nm,780～2 500 nm,400～2 500 nm范围内,所建模型表面粗糙度参数的实测值与预测值相关系数可达0.80以上,显著相关,其中400～2 500 nm区域所建模型效果最好;（3）光谱预处理并不能提高模型预测效果,建议利用可见光-近红外光谱预测天然高分子材料表面粗糙度时采用原始光谱数据。     

Textural changes during CO2 activation of chars: A fractal approach

In this paper two series of active carbons obtained at different flow rates of the activating agent, CO₂, are characterized in order to establish the different mechanisms of pore development during the activation step. This study complements previous works on textural development during the different steps in the process of obtaining active carbons: coal oxidation, coal pyrolysis and char gasification. As the characteristics of the original and intermediate materials are of capital importance in the pore development of active carbons, the properties of the active carbons, precursor chars and coals were considered and analyzed together. Mercury porosimetry and helium picnometry were used to determine classical textural parameters as well as to perform a more detailed study of the pore volume generation during the different conditions of the activation step. Data obtained from the mercury porosimetry determinations was also employed for fractal determinations according to the methodologies proposed by Friesen and Mikula, Zhang and Li and the procedure of Neimark. Average surface fractal dimensions as well as fractal profiles and local surface fractal dimensions were calculated. The use of different flow rates during the activation step produces changes not only in the ordinary textural parameters but also in the fractal characteristics of the active carbons. Activation at higher flow rates leads to smoother fractal profiles and also to lower values of the average surface fractal dimensions of the active carbons.     

Scale-dependent nature of the surface fractal dimension for bi- and multi-disperse porous solids by mercury porosimetry

The surface fractal dimension was calculated by using a mathematical model and mercury intrusion data for a variety of bi- and multi-disperse porous solids including silica gels, alumina pellets, and building stones. The mathematical model was obtained by modifying the well-established scaling relation published previously [Ind. Eng. Chem. Res., 34 (1995) 1383-1386]. It was also verified by comparing with the theoretical surface fractal dimensions for regular fractal structures (Skerpinski tetrahedron and Menger sponge) and the calculated surface fractal dimensions for silica gel and alumina particles via the linear fitting method established previously. The calculation results for various bi- and multi-disperse porous solids have demonstrated that the scale-dependent nature of the surface fractal dimension is ubiquitous. The difference in the surface fractal dimension between pore size intervals usually exists. The estimation of the surface fractal dimension on an average stand may lead to erroneous results.     

Surface roughness investigation of semi-conductor wafers

Conventionally, surface roughness is predominantly determined through the use of stylus instruments. However, there are certain limitations involved in the method, particularly when a test specimen, such as a silicon wafer, has a smooth mirror-like surface. Hence, it is necessary to explore alternative non-contact techniques. Light scattering has recently been gaining popularity as an optical technique to provide prompt and precise inspection of surface roughness. In this paper, the total integrated scattering (TIS) model is modified to retrieve parameters on surface micro-topography through light scattering. The applicability of the proposed modified TIS model is studied and compared with an atomic force microscope. Experimental results obtained show that the proposed technique is highly accurate for measuring surface roughness in the nanometer range.     

An optical method and neural network for surface roughness measurement

The measurement of surface roughness using stylus equipment has several disadvantages. A non-contact optical method is needed for measuring the surface roughness of engineering metals with improved accuracy. One candidate for an optical method is the use of a laser source, where the laser light intensity reflected from the surface represents the surface roughness of the illuminated area. A relation can be developed between the reflected laser beam intensity and the surface roughness of the metal. The present study examines the measurement of the surface roughness of the stainless steel samples using a He-Ne laser beam. In the measurement a Gaussian curve parameter of a Gaussian function approximating the peak of the reflected intensity is measured with a fast response photodetector. In order to achieve this, an experimental setup is designed and built. In the experimental apparatus, fiber-optic cables are used to collect the reflected beam from the surface. The output of the fiber-optic system is fed to a back-propagation neural network to classify the resulting surface profile and predict the surface roughness value. The results obtained from the present study are then compared with the stylus measurement results. It is found that the resolution of the surface texture improves considerably in the case of optical method and the neural network developed for this purpose can classify the surface texture according to the control charts developed mathematically.     

An optical method and neural network for surface roughness measurement

The measurement of surface roughness using the stylus equipment has several disadvantages. A non-contact optical method becomes demanding for measuring the surface roughness of the engineering metals with improved accuracy. One of the candidates for the optical method is the use of a laser source in which case the reflected laser light intensity from the surface may represent the surface roughness of the illuminated area. Consequently, a relation can be developed between the reflected laser beam intensity and the surface roughness of the metals. The present study examines the measurement of the surface roughness of the stainless-steel samples using a He–Ne laser beam. In the measurement, a Gaussian curve parameter of a Gaussian function approximating the peak of the reflected intensity is measured with a fast response photodetector. To achieve this, an experimental setup is designed and realized. In the experimental apparatus, fiber-optic cables are used to collect the reflected beam from the surface. The output of the fiber-optic system is fed to a backpropagation neural network to classify the resulting surface profile and predict the surface roughness value. The results obtained from the present study is, then, compared with the stylus measurement results. It is found that the resolution of the surface texture improves considerably in the case of optical method and the neural network developed for this purpose can classify the surface texture according to the control charts developed mathematically.     

Fractality of self-grown nanostructured tungsten by He plasma irradiation

Fractal property of the helium irradiated nanostructured tungsten was investigated from the scanning electron microscope (SEM) micrographs, gas adsorption isotherms, and transmission electron microscope (TEM) micrographs. From the SEM micrographs, fractal dimension and the parameter _dmin$d_{\min }$, which characterizes the SEM texture image, were deduced, and the fractal dimension was compared with the one obtained from the gas adsorption isotherms. It was revealed that the fractal dimension obtained from the top view SEM micrographs was significantly lower than that from the adsorption isotherms. From the cross sectional SEM micrographs, two power law relations were identified in two different scales, and the fractal dimension from the adsorption was in between the two fractal dimensions. From the TEM micrographs, it was found that the porosity distribution also has fractal relation with height of the nanostructures when the nanostructures were sufficiently grown.     

Non-contact adhesion to self-affine surfaces: A theoretical model

Strength of adhesion between materials is known to be strongly influenced by interface irregularities. In this work, I devise a perturbative approach to describe the effect of self-affine roughness on non-contact adhesive interactions. The hierarchy of the obtained analytical solutions is the following. First, analytical formulae are deduced to describe roughness corrections to the van der Waals interaction energies between a hemi-space adherend, bounded by a self-affine surface, and a point-like adherent. Second, the problem of two hemi-spaces, one of which has a planar surface, and the other is bounded by a self-affine surface, is solved analytically. In the latter case, a numerical analysis is performed to delineate the behavior of the roughness corrections as a function of the parameters, characterizing self-affine fractal surface roughness. The problem of two hemi-spaces, both bounded by self-affine fractal surfaces, is also addressed in this work. The model?s predictions are compared with previously reported theoretical results and available experimental data.     

Influences of Fractal Substrate Structures on Dynamic Scaling Behaviors of Etching Model

The Etching model on various fractal substrates embedded in two dimensions was investigated by means of kinetic Mento Carlo method in order to determine the relationship between dynamic scaling exponents and fractal parameters. The fractal dimensions are from 1.465 to 1.893, and the random walk exponents are from 2.101 to 2.578.It is found that the dynamic behaviors on fractal lattices are more complex than those on integer dimensions. The roughness exponent increases with the increasing of the random walk exponent on the fractal substrates but shows a non-monotonic relation with respect to the fractal dimension. No monotonic change is observed in the growth exponent.     

Effect of surface roughness of chitosan-based microspheres on cell adhesion

Microspheres are novel candidate materials for microcarriers and tissue-engineering scaffolds. Chitosan microspheres were selected as the base materials because of their excellent properties for biomedical applications. But their smooth surfaces were not adapted for cell attachment. Hence, in order to improve the roughness of chitosan microspheres, β-TCP/chitosan composite microspheres were developed. From SEM photographs, the coarse surfaces of composite microspheres were observed, there were some ceramic particles standing out of the chitosan matrix. And their roughness measured by profilometers was about 2.0 μm. Mouse MC3T3-E1 osteoblasts were seeded on the microspheres for evaluating the attachment interaction between cells and materials. According to the ESEM photographs and MTT assay, the adherence and proliferation of osteoblasts on the surfaces of modified microspheres were better than those on the chitosan microspheres, which were mainly attributed to the improved roughness of surface.     

Effect of surface lay in the surface roughness evaluation using machine vision

This work explores the influence of orientation of surface lay pattern of the machined components, while quantifying the surface roughness using machine vision approach. The surface images are captured from milled low carbon steel specimens with different roughness values using a vision system with coaxial lighting arrangement at different angular orientations of the work pieces (0°, 30°, 45°, 60°, 90°, 120°, 135°, 150°, and 180°). The captured images are subjected to preprocessing in order to retain the frequency components that attribute to roughness using a Gaussian filter by adapting the filtering procedures specified in ISO 4288. Numerous image based parameters such as gray level average (G_a), gray level co-occurrence matrix based image quantification parameters namely contrast, correlation, energy or uniformity, maximum probability and differential box courting based fractal dimension are computed from the surface images captured at different angular positions of the work piece. The computed vision based parameters are compared and correlated with the roughness average (R_a) obtained using a stylus instrument and the results are analyzed. The results clearly indicated that it is important to consider the orientation of the work piece when the machine vision approach is used to quantify the surface texture parameters.     

Molecular dynamics study of the equilibrium flux of gas molecules to a fractal/rough surface: Effects of gas atom diameter

The frequency of collisions of ideal gas molecules (argon) with a rough surface has been studied. The rough/fractal surface was created using the random deposition technique. By applying various depositions the surface roughness was controlled and, as a measure of irregularity, the fractal dimensions of the surfaces were determined. The surfaces were next immersed in ideal gas and the numbers of collisions with these surfaces were counted. The calculations were carried out using the simplified molecular dynamics simulation technique (only hard core repulsions were assumed). The calculations were performed for various ratios of gas phase atoms diameter to the surface substrate atoms diameter. The results obtained showed that the size of a gas phase atom has crucial influence on the relation between the frequency of collision and the surface fractal dimension     

Effects of Fractal Size Distributions on Velocity Distributions and Correlations of a Polydisperse Granular Gas

By the Monte Carlo method, the effect of dispersion of disc size distribution on the velocity distributions and correlations of a polydisperse granular gas with fractal size distribution is investigated in the same inelasticity. The dispersion can be described by a fractal dimension D, and the smooth hard discs are engaged in a two- dimensional horizontal rectangular box, colliding inelastically with each other and driven by a homogeneous heat bath. In the steady state, the tails of the velocity distribution functions rise more significantly above a Gaussian as D increases, but the non-Gaussian velocity distribution functions do not demonstrate any apparent universal form for any value of D. The spatial velocity correlations are apparently stronger with the increase of D. The perpendicular correlations are about half the parallel correlations, and the two correlations are a power-law decay function of dimensionless distance and are of a long range. Moreover, the parallel velocity correlations of postcollisional state at contact are more than twice as large as the precollisional correlations, and both of them show almost linear behaviour of the fractal dimension D.     

The study of fractal correlation method in the displacement measurement and its application

The classical digital speckle, or digital image, correlation method of deformation measurement is based on gray level correlation between unformed and deformed digital images. The pattern of artificial random speckles and the natural textures on some object's surfaces have fractal characteristics, and their fractal dimensions represent both gray and morph information. Furthermore, the fractal dimensions are stable feature parameters of the patterns. The digitized images of the patterns are confirmed to be also fractals. By this fact, a new method of displacement measurement is developed in the paper, based on the fractal dimensions correlation. The in-plane displacement fields of a body can be acquired. In order to verify the validity of the new method, an experiment has been designed and the results have been compared with those obtained from the classical digital image correlation method. The validity of the new method is not less than that of classical method. Further discussions about the traits and the developing vista of the method are given at the end.     

Self-affinity study of nanostructured porous silicon-crystalline silicon interfaces

Self-affinity was used to analyze the roughness at the porous silicon (PS)-crystalline Si (cSi) interfaces fabricated under different conditions. Using the variable bandwidth method, the self-affinity behavior was, qualitatively and quantitatively, analyzed from the cross-section micrographs of the PS samples obtained by field emission scanning electron microscope. The results show that correlation length is related with the average pore width. Roughness exponent is found to be correlated with the interface roughness. In addition, similar experimental roughness exponents were obtained for several interfaces grown by different methods, indicating the intrinsic fractal nature of the PS-cSi interfaces. The results were confirmed through the self-affinity analysis done on the atomic force microscopy profiles.     

Rapid in-process measurement of surface roughness using adaptive optics

We present an in-process measurement of surface roughness by combining an optical probe of laser-scattering phenomena and adaptive optics for aberration correction. Measurement results of five steel samples with a roughness ranging from 0.2 to 3.125 μm demonstrate excellent correlation between the peak power and average roughness with a correlation coefficient (R(2)) of 0.9967. The proposed adaptive-optics-assisted system is in good agreement with the stylus method, and error values of less than 8.7% are obtained for average sample roughness in the range of 0.265 to 1.119 μm. The proposed system can be used as a rapid in-process roughness monitor/estimator to further increase the precision and stability of manufacturing processes in situ.     

规则表面形貌的分形和多重分形描述

以6种具有典型特征的生成元构造了6个具有相同rms粗糙度的规则表面,用变分法计算了这些表面的分形维数,结果表明,分形维数可以将具有相同rms粗糙度的表面区分开来,它定量表征了表面的总体形貌。进一步将多重分形的方法应用到对这些表面的分析中,发现多重分形谱可以全面反映表面概率的分布特征。多重分形谱的宽度可以定量表征表面的起伏程度,多重分形谱最大、最小概率子集维数的差别可以统计表面最大、最小概率处的数目比例。 关键词： 粗糙度 分形维数 多重分形谱